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MLSMM: Machine Learning Security Maturity Model

Year: 2023

Type: preprint

Abstract: Assessing the maturity of security practices during the development of Machine Learning (ML) based software components has not gotten as much attention as traditional software development. In this Blue Sky idea paper, we propose an initial Machine Learning Security Maturity Model (MLSMM) which organizes security practices along the ML-development lifecycle and, for each, establishes three levels of maturity. We envision MLSMM as a step towards closer collaboration between industry and academia.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2306.16127

Authors: Jedrzejewski, Felix, Fucci, Davide, Adamov, Oleksandr

Language: English

Topic: Adversarial Robustness in Machine Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4382618854

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